ComfyUI Extension: ComfyUI_LLM_Embeder
Run ComfyUI workflows without the setup
No installs, no CUDA version roulette, no GPU sitting idle on your bill. Bring a workflow and run it in the browser.
Local LLM chat nodes for ComfyUI, with a clean handoff path to downstream prompt optimization.
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README
ComfyUI-LLM-Embeder
Local LLM chat nodes for ComfyUI, with a clean handoff path to downstream prompt optimization.
Features
- Multi-turn chat with Ollama
/api/chat - Optional Hugging Face Inference API support via LLM Config
- OpenAI-compatible chat support (OpenAI / DeepSeek / Qwen) via custom
base_url - Anthropic Claude support via custom
base_url - Session memory by
session_id(in-memory only) - Optional
system_prompt - Scrollable history in a modal viewer
deliver_to_optimizeraction outputs the latest assistant reply only- Auto-clear input after send (toggle)
Nodes
Chat (Ollama)
Inputs:
model_name: model id (Ollama or HF, depending on provider)base_url: Ollama base URL (ignored when provider ishuggingface)user_message: user input textaction:send/regenerate/clear/deliver_to_optimizersession_id: conversation idsystem_prompt: system messagerefresh_session: reset history for the session idauto_clear_input: clear input after a successful sendllm_config: optional config from LLM Config node
Outputs:
assistant_response: only non-empty whenaction=deliver_to_optimizerreadable_history: full readable transcript
Behavior:
send: appends user input, calls the provider, updates historyregenerate: drops the last assistant turn, calls the provider againclear: resets history (keeps system prompt if set)deliver_to_optimizer: does not call the provider; returns the latest assistant reply from history
LLM Config
Outputs a LLM_CONFIG struct that can be shared across Chat nodes.
Fields:
provider:ollama,huggingface,openai,deepseek,qwen,claudebase_url: provider base URL (see sections below)model_name: model name or model id (provider specific)temperaturetop_pmax_new_tokenshf_token: Hugging Face API token (recommended)hf_api_url: optional override for Hugging Face Inference API endpointapi_key: API key for OpenAI-compatible or Anthropic providers
Chat History Viewer
Shows readable_history and provides an "Open History" modal for full scroll.
Hugging Face Inference API
When provider=huggingface, the Chat node will call:
https://api-inference.huggingface.co/models/{model_name}
Notes:
- Many public models still require an HF token.
- Chat history is converted into a single prompt before the API call.
OpenAI-Compatible API (OpenAI / DeepSeek / Qwen)
When provider=openai|deepseek|qwen, the Chat node will call:
{base_url}/chat/completions
Notes:
- Use an OpenAI-compatible base URL for your provider.
- Set
api_keyin LLM Config. model_nameshould be the provider's model id.
Anthropic Claude API
When provider=claude, the Chat node will call:
{base_url}/v1/messages
Notes:
- Use an Anthropic-compatible base URL.
- Set
api_keyin LLM Config.
Install
- Place this folder under
ComfyUI/custom_nodes/ - Restart ComfyUI
- Add nodes:
Chat (Ollama)LLM ConfigChat History Viewer
Usage
- Create
Chat (Ollama)and setbase_url/model_name - (Optional) Add
LLM Configto select provider and setapi_key - Set
action=send, click Execute to chat - When satisfied, set
action=deliver_to_optimizerand Execute - Use
assistant_responseoutput to feed your optimizer node
Screenshot

Example graph: LLM Config drives Chat (Ollama) via llm_config, and outputs route to a text node plus Chat History Viewer for full history review.
Example Workflow

Drag this image into ComfyUI to load and run the workflow.
API
Frontend calls POST /chat_optimize/chat and receives:
assistant_responsereadable_history
Notes
- History is in memory only; refresh or restart clears it.
assistant_responseis empty for all actions exceptdeliver_to_optimizer.- If new fields do not appear, restart ComfyUI and re-add the node.
Contact
For questions or collaboration, email: [email protected].
License
MIT. See LICENSE.
Run ComfyUI workflows without the setup
No installs, no CUDA version roulette, no GPU sitting idle on your bill. Bring a workflow and run it in the browser.